Discriminant Regression Analysis to Find Homogeneous Structures View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009

AUTHORS

Esteban Garcia-Cuesta , Ines M. Galvan , Antonio J. de Castro

ABSTRACT

The main motivation of this paper is to propose a method to extract the structure information from the output data and find the input data manifold that best represents that output structure. A graph similarity viewpoint is used to build up a clustering algorithm that tries to find out different linear models in a regression framework. The main novelty of the algorithm is related with using the structured information of the output data, to find out several input models that best represent that structure. This novelty is base on the intuition that similar structures in the output must share a common model. Finally, the proposed method is applied to a real remote sensing retrieval problem where we want to recover the physical parameters from a spectrum of energy. More... »

PAGES

191-199

References to SciGraph publications

Book

TITLE

Intelligent Data Engineering and Automated Learning - IDEAL 2009

ISBN

978-3-642-04393-2
978-3-642-04394-9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-04394-9_24

DOI

http://dx.doi.org/10.1007/978-3-642-04394-9_24

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009525899


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